code: def __init__(
      self, num_users, num_items, hidden_channels, out_channels
  ):
      super().__init__()
      self.user_emb = Embedding(
          num_users, hidden_channels, device=device
      )
      self.item_emb = Embedding(
          num_items, hidden_channels, device=device
      )
      self.item_encoder = ItemGNNEncoder(hidden_channels, out_channels)
      self.user_encoder = UserGNNEncoder(hidden_channels, out_channels)
      self.decoder = EdgeDecoder(out_channels)
  
imports: import os.path
  import torch
  import torch.nn.functional
  import tqdm
  from sklearn.metrics import roc_auc_score
  from torch.nn import Embedding, Linear
  import torch_geometric.transforms
  from torch_geometric.datasets import Taobao
  from torch_geometric.loader import LinkNeighborLoader
  from torch_geometric.nn import SAGEConv
  from torch_geometric.utils.convert import to_scipy_sparse_matrix
label_desc: Use image node_id 1 to create a new Model object from inherited base classes: torch.nn with example: obj = Model(num_users, num_items, hidden_channels, out_channels)